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tangled-llama-pints-1.5b-v0.2-instruct

PEFT
PyTorch
Safetensors
llama
Generated from Trainer
Model card Files Community
2
tangled-llama-pints-1.5b-v0.2-instruct
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---

base_model: pints-ai/1.5-Pints-16K-v0.1
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: tangledgroup/tangled-llama-pints-1.5b-v0.2-instruct
  results: []
datasets:
- tangledgroup/tangled-llama-pints-1.5b-v0.2-dataset
---


<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml

base_model: pints-ai/1.5-Pints-16K-v0.1

model_type: AutoModelForCausalLM

tokenizer_type: AutoTokenizer



load_in_8bit: false

load_in_4bit: true

strict: false



datasets:

  - path: tangledgroup/tangled-llama-pints-1.5b-v0.2-dataset

    type: sharegpt

    conversation: chatml

chat_template: chatml

dataset_prepared_path:

val_set_size: 0.05

output_dir: ./outputs/qlora-out



adapter: qlora

lora_model_dir:



sequence_len: 16384

sample_packing: true

pad_to_sequence_len: true



lora_r: 32

lora_alpha: 16

lora_dropout: 0.05

lora_target_modules:

lora_target_linear: true

lora_fan_in_fan_out:



wandb_project:

wandb_entity:

wandb_watch:

wandb_name:

wandb_log_model:



gradient_accumulation_steps: 4

micro_batch_size: 2

num_epochs: 3

optimizer: paged_adamw_32bit

# optimizer: adamw_torch_fused

lr_scheduler: cosine

learning_rate: 0.0002



train_on_inputs: false

group_by_length: false

bf16: auto

fp16:

tf32: false



gradient_checkpointing: true

early_stopping_patience:

resume_from_checkpoint:

local_rank:

logging_steps: 1

xformers_attention:

flash_attention: true



loss_watchdog_threshold: 15.0

loss_watchdog_patience: 3



warmup_steps: 10

evals_per_epoch: 3

eval_table_size:

saves_per_epoch: 1

debug:

deepspeed:

weight_decay: 0.0

fsdp:

fsdp_config:

special_tokens:



plugins:

- axolotl.integrations.liger.LigerPlugin

liger_rope: true

liger_rms_norm: true

liger_swiglu: true

liger_fused_linear_cross_entropy: true

```

</details><br>

# outputs/qlora-out

This model is a fine-tuned version of [pints-ai/1.5-Pints-16K-v0.1](https://huggingface.co/pints-ai/1.5-Pints-16K-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9847

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002

- train_batch_size: 2

- eval_batch_size: 2

- seed: 42

- gradient_accumulation_steps: 4

- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10

- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1396        | 0.0011 | 1    | 1.1313          |
| 1.0777        | 0.3332 | 295  | 1.0278          |
| 1.0219        | 0.6665 | 590  | 1.0119          |
| 1.0006        | 0.9997 | 885  | 1.0020          |
| 1.0385        | 1.3307 | 1180 | 0.9954          |
| 0.9405        | 1.6639 | 1475 | 0.9902          |
| 0.9249        | 1.9972 | 1770 | 0.9867          |
| 0.9951        | 2.3282 | 2065 | 0.9856          |
| 0.9713        | 2.6616 | 2360 | 0.9848          |
| 0.9576        | 2.9949 | 2655 | 0.9847          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.19.1
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_tangledgroup__tangled-llama-pints-1.5b-v0.2-instruct)

|      Metric       |Value|
|-------------------|----:|
|Avg.               | 4.66|
|IFEval (0-Shot)    |17.24|
|BBH (3-Shot)       | 4.08|
|MATH Lvl 5 (4-Shot)| 0.76|
|GPQA (0-shot)      | 0.00|
|MuSR (0-shot)      | 4.57|
|MMLU-PRO (5-shot)  | 1.30|